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Derek Wright, Sandesh Neupane, Taryn Heidecker, Teketel Haile, Clarice Coyne, Sripada Udupa, Eleonora Barilli, Diego Rubiales, Tania Gioia, Reena Mehra, Ashutosh Sarker, Rajeev Dhakal, Babul Anwar, Debashish Sarker, Albert Vandenberg, and Kirstin E. Bett

AGILE Project

Collaborators

  • Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
  • United States Department of Agriculture Western Region Plant Introduction Station, Pullman, Washington, USA
  • International Center for Agriculture Research in the Dry Areas, Rabat, Morocco
  • Institute for Sustainable Agriculture, Spanish National Research Council, Cordoba, Spain
  • School of Agriculture, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
  • International Center for Agriculture Research in the Dry Areas, New Delhi, India
  • Local Initiatives for Biodiversity, Research and Development, Pokhara, Nepal
  • Bangladesh Agricultural Research Institute, Jessore, Bangladesh

Sponsors

  • Saskatchewan Pulse Growers Association
  • Western Grains Research Foundation
  • GenomePrairie
  • GenomeCanada
  • Saskatchewan Ministry of Agriculture

Shiny App

Download this folder and run app.R in R

or visit https://derek-wright-usask.shinyapps.io/AGILE_LDP_Phenology/

Figures

Figure 1

Fig 1: (a) Locations of field trials conducted in the summer and winter of 2016, 2017 and 2018, along with (b) mean temperature and photoperiod of each field trial: Rosthern, Canada 2016 and 2017 (Ro16, Ro17), Sutherland, Canada 2016, 2017 and 2018 (Su16, Su17, Su18), Central Ferry, USA 2018 (Us18), Metaponto, Italy 2016 and 2017 (It16, It17), Marchouch, Morocco 2016 and 2017 (Mo16, Mo17), Cordoba, Spain 2016 and 2017 (Sp16, Sp17), Bhopal, India 2016 and 2017 (In16, In17), Jessore, Bangladesh 2016 and 2017 (Ba16, Ba17), Bardiya, Nepal 2016 and 2017 (Ne16, Ne17).

Figure 2

Fig. 2: (a) Daily mean temperature (red line) and day length (blue line) from seeding to full maturity of all genotypes. The shaded ribbon represents the daily minimum and maximum temperature. The shaded area between the vertical bars corresponds to the windows of flowering. (b) Distribution of mean days from sowing to: flowering (DTF), swollen pods (DTS) and maturity (DTM), and (c) vegetative (VEG) and reproductive periods (REP) of 324 genotypes across 18 site-years. Rosthern, Canada 2016 and 2017 (Ro16, Ro17), Sutherland, Canada 2016, 2017 and 2018 (Su16, Su17, Su18), Central Ferry, USA 2018 (Us18), Metaponto, Italy 2016 and 2017 (It16, It17), Marchouch, Morocco 2016 and 2017 (Mo16, Mo17), Cordoba, Spain 2016 and 2017 (Sp16, Sp17), Bhopal, India 2016 and 2017 (In16, In17), Jessore, Bangladesh 2016 and 2017 (Ba16, Ba17), Bardiya, Nepal 2016 and 2017 (Ne16, Ne17).

Figure 3

Fig. 3: (a) Principal Component Analysis on days from sowing to flower (DTF), scaled from 1-5, and hierarchical k-means clustering into eight groups. (b) Mean scaled DTF (1-5) for each cluster group across all field trials: Rosthern, Canada 2016 and 2017 (Ro16, Ro17), Sutherland, Canada 2016, 2017 and 2018 (Su16, Su17, Su18), Central Ferry, USA 2018 (Us18), Metaponto, Italy 2016 and 2017 (It16, It17), Marchouch, Morocco 2016 and 2017 (Mo16, Mo17), Cordoba, Spain 2016 and 2017 (Sp16, Sp17), Bhopal, India 2016 and 2017 (In16, In17), Jessore, Bangladesh 2016 and 2017 (Ba16, Ba17), Bardiya, Nepal 2016 and 2017 (Ne16, Ne17). Shaded areas represent one standard deviation from the mean. Dashed, vertical bars separate temperate, South Asian and Mediterranean macro-environments. (c) Composition of cluster groups in genotypes by country of origin. Pie size is relative to the number of genotypes originating from that country.

Figure 4

Fig. 4: Comparison of observed and predicted values, along with the coefficient of determination (R2) and root-mean-square error (RMSE), for days from sowing to flowering, calculated using equation 1. For each site year, the model was retrained after removing all observations from that location, regardless of year before predicting results from that location.

Figure 5

Fig. 5: (a) Distribution of a, b and c constants derived from equation 1 among cluster groups. Estimates of: (b) nominal base temperature (Tb), and (c) nominal base photoperiod (Pc) based on equations 2 and 3, respectively, using the mean temperature (T) and photoperiod (P) from Sutherland, Canada 2017, Jessore, Bangladesh 2017 and Metaponto, Italy 2017.

Figure 6

Fig. 6: Mean values for genotypes of different origins. (a) Comparison of days from sowing to flowering in Sutherland, Canada 2017 and the genotype constant a (x 104) derived from equation 1. (b) Comparison of temperature response (b x 104) and photoperiod response (c x 104) derived from equation 1. Polygons represent the variation inherent in the region where the crop was domesticated.

Figure 7

Fig. 7: Predicted decrease in days from sowing to flowering based on a mean temperature (T) or photoperiod (P) increases of 0.1h or and 1.5oC using equation 1 in the selected locations: Rosthern, Canada 2017 (Ro17), Sutherland, Canada 2017 (Su17), Central Ferry, USA 2018 (Us18), Bhopal, India 2017 (In17), Jessore, Bangladesh 2017 (Ba17), Bardiya, Nepal 2017 (Ne17), Marchouch, Morocco 2017 (Mo17), Cordoba, Spain 2017 (Sp17) and Metaponto, Italy 2017 (It17).

Supplemental Figures

Supplemental Figure 1

Fig. S1: Distribution of days from sowing to flowering for raw data (top) and scaled data (1-5) (bottom) for all 18 field trials: Rosthern, Canada 2016 and 2017 (Ro16, Ro17), Sutherland, Canada 2016, 2017 and 2018 (Su16, Su17, Su18), Central Ferry, USA 2018 (Us18), Metaponto, Italy 2016 and 2017 (It16, It17), Marchouch, Morocco 2016 and 2017 (Mo16, Mo17), Cordoba, Spain 2016 and 2017 (Sp16, Sp17), Bhopal, India 2016 and 2017 (In16, In17), Jessore, Bangladesh 2016 and 2017 (Ba16, Ba17), Bardiya, Nepal 2016 and 2017 (Ne16, Ne17). Genotypes which did not flower were given a scaled value of 5.

Supplemental Figure 2

Fig. S2: Percentage of lentil genotypes reaching key phenological time points in South Asian locations. Days from sowing to: flowering (DTF), swollen pods (DTS) and maturity (DTM).

Supplemental Figure 3

Fig. S3: Correlations along with the corresponding correlation coefficients (R2) between days from sowing to: flowering (DTF), swollen pod (DTS) and maturity (DTM), in temperate (top), South Asian (middle) and Mediterranean (bottom) locations.

Supplemental Figure 4

Fig. S4: Effects of mean temperature and photoperiod on the rate of progress towards flowering (1 / DTF) in three contrasting selected genotypes. (a) Effect of temperature on 1 / DTF, (b) effect of photoperiod on 1 / DTF, and (c) effect of temperature and photoperiod on 1 / DTF modelled using equation 1. For (a) and (b), solid lines represent regressions among locations of relatively constant photoperiod or temperature, respectively, while dotted lines indicate a break in the assumption of constant photoperiod or temperature, respectively, across environments (see Figure 1). (d) Scaled DTF (1-5) of each genotype (grey lines) across all site-years with ILL5888, PI 420925 LSP and Laird highlighted according to their corresponding cluster group, 1, 5 and 8 respectively. ILL 5888 is an early maturing, genotype from Bangladesh. PI 420925 LSP is a landrace from Jordan with medium maturity. Laird is a late maturing, Canadian cultivar.

Supplemental Figure 5

Fig. S5: Comparison of observed and predicted values for days from sowing to flowering using (a) equation 1 and (b) equation 2.

Supplemental Figure 6

Fig. S6: Comparison of a, b, and c constants calculated using equation 1, in the current study using all site-years, the three best site-years for predicting DTF, Sutherland, Canada 2016 (Su16), Jessore, Bangladesh 2017 (Ba17) and Cordoba, Spain 2017 (Sp17), the three worst site-years for predicting DTF, Sutherland, Canada 2018 (Su18), Bhopal, India 2016 (In16) and Cordoba, Spain 2016 (Sp16), from Roberts et al., (1988) and from Summerfield et al., (1985) with (+V) and without (-V) a seed vernalization treatment.

Supplemental Figure 7

Fig. S7: Comparison of observed and predicted values, along with the coefficient of determination (R2) and root-mean-square error (RMSE), for days from sowing to flowering, calculated using equation 1, with (a) the 3 best site-years for training the model and (b) the 3 worst years for training the model (see Table S4). Sutherland, Canada 2016 and 2018 (Su16, Su18), Cordoba, Spain 2016 and 2017 (Sp16, Sp17), Bhopal, India 2016 (In16) and Jessore, Bangladesh 2017 (Ba17). Predictions of DTF can only be made with genotypes that flowered in all three locations, therefore, predictions in (a) are based on 291 and in (b) based on 159 of 324 genotypes used in this study.

Supplemental Figure 8

Fig. S8: Comparison of a, b, and c constants calculated using equation 1 using all site-years, the three best site-years for predicting DTF, Sutherland, Canada 2016 (Su16), Jessore, Bangladesh 2017 (Ba17) and Cordoba, Spain 2017 (Sp17), and the three worst site-years for predicting DTF, Sutherland, Canada 2018 (Su18), Bhopal, India 2016 (In16) and Cordoba, Spain 2016 (Sp16).

Supplemental Figure 9

Fig. S9: (a) Thermal sum required for flowering (Tf), using a base temperature (Tb) of 0°C, 5°C and calculated using equation 3, across all site-years. (b) Photoperiodic sum required for flowering (Pf), using a critical photoperiod (Pc) of 0h, 5h and calculated using equation 4, across all site-years. Rosthern, Canada 2016 and 2017 (Ro16, Ro17), Sutherland, Canada 2016, 2017 and 2018 (Su16, Su17, Su18), Central Ferry, USA 2018 (Us18), Metaponto, Italy 2016 and 2017 (It16, It17), Marchouch, Morocco 2016 and 2017 (Mo16, Mo17), Cordoba, Spain 2016 and 2017 (Sp16, Sp17), Bhopal, India 2016 and 2017 (In16, In17), Jessore, Bangladesh 2016 and 2017 (Ba16, Ba17), Bardiya, Nepal 2016 and 2017 (Ne16, Ne17).

Supplemental Figure 10

Fig. S10: Comparison of observed vs predicted values, along with the coefficient of determination (R2) and root-mean-square error (RMSE), for (a) thermal sum required for flowering and (b) days from sowing to flowering, calculated using equation 5.

Supplemental Figure 11

Fig. S11: Comparison of observed vs predicted values, along with the coefficient of determination (R2) and root-mean-square error (RMSE) for (a) photoperiodic sum required for flowering and (b) days from sowing to flowering, calculated using equation 6.

Supplemental Tables

Supplemental Table 1

Entry Name Origin Source Synonyms
1 1 CDC Asterix AGL Canada USASK
2 2 CDC Rosie AGL Canada USASK
3 3 3156-11 AGL Canada USASK
4 4 CDC Greenstar AGL Canada USASK
5 5 CDC Cherie AGL Canada USASK
31 31 CN 105777 AGL Egypt PGRC LENS 170;B 47
32 32 CN 105789 AGL Ethiopia PGRC LENS 184;B 136
33 33 CN 105791 AGL Egypt PGRC LENS 190;B 32
34 34 CN 105862 AGL Tunisia PGRC LENS 559
35 35 CN 105863 AGL Tunisia PGRC LENS 561
101 101 ILL 6821 AGL Ethiopia ICARDA IG 73685;FLIP 89-63L;ALEMAYA
102 102 ILL 6853 AGL Syria ICARDA IG 73717
103 103 ILL 7089 AGL Russia ICARDA IG 73953
104 104 ILL 7558 AGL India ICARDA IG 76277
105 105 ILL 7663 AGL ICARDA ICARDA IG 114665;FLIP 95-7L
320 320 W6 27754 LSP AGL USDA USDA
321 321 W6 27760 LSP AGL USDA USDA
322 322 W6 27763 LSP AGL USDA USDA
323 323 W6 27766 LSP AGL USDA USDA
324 324 W6 27767 LSP AGL USDA USDA Not Barimasur-4

Table S1: Genotype entry number, name, common synonyms, origin and source of lentil genotypes used in this study. These genotypes are gathered from the University of Saskatchewan (USASK), Plant Gene Resources of Canada (PGRC), United States Department of Agriculture (USDA), International Center for Agricultural Research in the Dry Areas (ICARDA).

Supplemental Table 2

Location Year Short.Name Latitude Longitude Planting.Date Temperature..mean. Photoperiod..mean. Number.of.Seeds.Sown Plot.Type
Sutherland, Canada 2016 Su16 52.16770 -106.5054 2016-04-27 16.7 15.9 60 three, 1 meter rows
Rosthern, Canada 2016 Ro16 52.68920 -106.2945 2016-05-06 17.2 16.2 60 three, 1 meter rows
Marchouch, Morocco 2016 Mo16 33.62000 -6.7200 2016-11-21 12.0 10.8 25 one, 1 meter row
Cordoba, Spain 2016 Sp16 37.90000 -4.8000 2016-12-13 12.5 10.9 25 one, 1 meter row
Metaponto, Italy 2016 It16 40.39000 16.7800 2016-11-29 10.6 10.8 25 one, 1 meter row
Bhopal, India 2016 In16 23.11000 76.8800 2016-12-04 17.6 10.9 25 one, 1 meter row
Bardiya, Nepal 2016 Ne16 28.25000 81.5000 2016-11-14 19.2 11.0 25 one, 1 meter row
Jessore, Bangladesh 2016 Ba16 23.19000 89.1900 2016-11-15 18.6 10.8 25 one, 1 meter row
Sutherland, Canada 2017 Su17 52.16832 -106.5108 2017-05-04 15.7 16.1 70 three, 1 meter rows
Rosthern, Canada 2017 Ro17 52.69150 -106.2897 2017-05-19 17.5 16.4 70 three, 1 meter rows
Marchouch, Morocco 2017 Mo17 33.62000 -6.7200 2017-12-21 11.8 11.5 50 two, 1 meter rows
Cordoba, Spain 2017 Sp17 37.90000 -4.8000 2017-12-14 11.7 11.1 50 two, 1 meter rows
Metaponto, Italy 2017 It17 40.39000 16.7800 2017-11-28 11.2 10.8 50 two, 1 meter rows
Bhopal, India 2017 In17 23.11500 76.8850 2017-11-09 20.6 10.7 50 two, 1 meter rows
Jessore, Bangladesh 2017 Ba17 23.19500 89.1950 2017-12-03 21.7 11.0 50 two, 1 meter rows
Central Ferry, USA 2018 Us18 46.65000 -117.7600 2018-03-29 15.8 14.3 50 two, 1 meter rows
Sutherland, Canada 2018 Su18 52.16890 -106.5149 2018-05-09 17.6 16.1 70 three, 1 meter rows
Bardiya, Nepal 2017 Ne17 28.42000 81.8600 2017-11-03 19.4 10.8 50 two, 1 meter rows

Table S2: Details of the field trials used in this study, including location information, planting dates, mean temperature and photoperiods and details on plot type and number of seeds sown.

Supplemental Table 3

Entry Name a b c d RR Environments a_p.value b_p.value c_p.value d_p.value
1 1 CDC Asterix AGL -0.0187717 0.0003372 0.0020456 NA 0.8978347 16 0.0000000 0.0000001 0.0000000 NA
2 1 CDC Asterix AGL 0.0072693 -0.0012017 -0.0003174 0.0001397 0.8992827 16 0.6202032 0.1688352 0.8110850 0.0793975
61 31 CN 105777 AGL -0.0203402 0.0006260 0.0020791 NA 0.8417776 18 0.0000000 0.0000000 0.0000000 NA
62 31 CN 105777 AGL -0.0299805 0.0011958 0.0029539 -0.0000518 0.8473458 18 0.1417083 0.3178702 0.1107758 0.6321050
201 101 ILL 6821 AGL -0.0207765 0.0001801 0.0024844 NA 0.9055885 14 0.0000000 0.0006591 0.0000000 NA
202 101 ILL 6821 AGL -0.0149886 -0.0001621 0.0019592 0.0000311 0.9051060 14 0.2937562 0.8467141 0.1321410 0.6828037
647 324 W6 27767 LSP AGL -0.0194010 0.0002353 0.0022805 NA 0.8697454 15 0.0000000 0.0000289 0.0000000 NA
648 324 W6 27767 LSP AGL -0.0080395 -0.0004354 0.0012494 0.0000609 0.8679062 15 0.5871621 0.6178443 0.3531932 0.4421900

Table S3: Values of the constants derived from equations 1 and 2 using data from all site-years, for each of the genotypes used in this study.

Supplemental Table 4

Temperate_Location SouthAsian_Location Mediterranean_Location RR Genotypes
1 Ro17 In16 Sp16 0.461770 159
2 Su18 In16 Sp16 0.462242 159
3 Ro16 In16 Sp16 0.466809 159
4 Su17 In16 Sp16 0.469932 159
5 Su16 In16 Sp16 0.473691 159
6 Ro17 In16 It17 0.475920 159
211 Ro17 Ba17 Sp17 0.858843 291
212 Su16 Ba17 Mo16 0.858923 291
213 Ro16 Ba17 Sp17 0.859936 291
214 Us18 Ba17 Sp17 0.861168 289
215 Su17 Ba17 Sp17 0.862977 291
216 Su16 Ba17 Sp17 0.863054 291

Table S4: All possible combinations of a single temperate, South Asian, and Mediterranean site-year, used to train the model, with equation 1, along with the corresponding coefficient of determination (RR = R2), and number of genotypes which flowered in all three site-years.

Additional Figures

Additional Figure 1

Additional Figure 2

Additional Figure 3

Additional Figure 4

Additional Figure 6

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Additional Figure 8

Additional Figure 9

Additional Figure 10

Additional Figure 11

Additional Figure 12

Additional Figure 13

Additional Figure 14

Phothermal Animation

Temperature and Photoperiod Regressions

pdf of Temperature and Photoperiod Regressions

Model Predictions

pdf of Model Predictions

Photothermal Planes

pdf of Photothermal Planes